Interactively Exploring Time-Oriented Data

Time is an important data dimension with distinct characteristics that is common across many application domains. This demands specialized methods in order to support proper analysis and visualization to explore trends, patterns, and relationships in different kinds of time-oriented data. The human perceptual system is highly sophisticated and specifically suited to spot visual patterns. For this reason, visualization is successfully applied in aiding these tasks and to date a variety of different visualization methods for time-oriented data exist. However, these methods could be improved by accounting for the special characteristics of time. The main aim of our current research is to account for the complex structures of time in visual representations, analysis, and the visualization process. Especially important are interaction methods that aid analysts when dealing with time-oriented data in visualization systems.